Detecting DNA Mutations: Hands-on Variant Analysis using Galaxy (Beginner-Friendly)
Master hands-on variant analysis to accurately identify genetic abnormalities using Galaxy pipelines. Learn to identify pathogenic genomic shifts and structural variations through advanced bioinformatics analysis.
- 5.0/5
- English
- Updated Aug 2026
About this course
This intensive online workshop focuses on detecting DNA mutations through standard modern bioinformatics pipelines. Participants will dive directly into real-world dataset evaluation to master hands-on variant analysis using the open-source Galaxy platform. The curriculum covers the entire genomic pipeline from processing raw sequencing reads to isolating complex genetic polymorphisms and variants. By leveraging algorithmic workflows and digital data-mapping logic, you will learn how to automate sequence alignment and filtering steps. This training bridges the gap between massive molecular data streams and actionable biological insights without needing a programming background. You will discover how to identify Single Nucleotide Polymorphisms (SNPs), insertions, deletions, and disease-causing genomic anomalies efficiently. By the end of this session, you will possess a clear understand of how computational tools index structural biological alterations. Elevate your bioinformatics expertise, understand machine-readable data structures, and accelerate your life science research insights.
What you will learn
Skills you will gain
Certification
Available
Issued by Dr. OmicsCourse curriculum
1 moduleWhat you need to start
- Basic, foundational understanding of DNA structure, genetics, and molecular biology concepts.
- No complex programming experience, command-line skills, or coding history is required.
Who this course is for
- Life science students, medical researchers, and laboratory technicians working with genomic data.
- Molecular biologists and clinicians aiming to pick up computational variant analysis skills.
- Bioinformatics enthusiasts looking to run zero-code, reproducible genomic data analysis pipelines.